{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Example 2.9:** Image rotation and intensity interpolation.\n",
    "\n",
    "This includes figure 2.36\n",
    "\n",
    "> This code is written with Julia v1.0.0, Images v0.16.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Printf # format string in C style\n",
    "using Images # core package for image\n",
    "using CoordinateTransformations, Interpolations # for image rotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "summary(img_ori) = \"540×420 Array{Gray{Float32},2} with eltype Gray{Float32}\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "540×420 Array{Gray{Float32},2} with eltype Gray{Float32}:\n",
       " Gray{Float32}(0.0)        …  Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)        …  Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)        …  Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0)           Gray{Float32}(0.0)       \n",
       " ⋮                         ⋱                           \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)  …  Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)  …  Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0)       \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.00392157)\n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0980392) \n",
       " Gray{Float32}(0.0980392)     Gray{Float32}(0.0980392) "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_ori = load(\"Data/Fig0236(a)(letter_T).tif\") .|> float32 # use Float32 to avoid unwanted overflow in N0f8\n",
    "@show summary(img_ori)\n",
    "\n",
    "img_ori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HBp+k53nj/8Gf9FTXrOtgLY9wWKG/Xndq9IYferaxVO+xB79a+8mUjfaPcIBD0vvMcK6+4XMNGhsiHHQDW/WKHmGQGd1pqq1dF5hem1GOgjwIXPDxuXqu2MV6oJzcvXhS4IjNIxzgkGL2xN9cBK6Zmksi7+OYJuWNLqVi+e1Pp+zruHO0tnZegNsJn4IISErZQ0/ru2CX6E/4yOYZk5bYOsIBDilhTmxlJXDLhKyHCz0In1QoQV7/sv+5WgctGiqU2tptgcAmjaMoFiIgKX1eGJF9giRLiuLlIkGeG0ii3mtqrF0xddou+0Y4wCEJnUYQYuyu13JSyP5Fy1UdLikXoVzHS2//a+vsMkrYc+i0Iw1nBEOtsguqHz1ZW7ssEKhTP4jS3AQkxXv3cyWaMyRFCntlj+zhUeF1baLagj5JZiSvJJ+onjdxTqNNIxx8uRlCAgQiBCIvUc72WTpgwp9+8mrgsXlvzZn3D3b01GyyqsdGMzaTsctVj6FQhEDfkVn8UUg5IG89cGSbsqOsbePZ54XajvQonUS0Jsm0Pvfcyst/FAgsSyrDJoGApFRcXaLxEJIsSXx+cGRX9d7toV2etqxL95LSEaeEvR4mB33isfyeUy7sc/O6T6esD/L0qyGF0DkriBo0Q3p8jBUGZ34f/vCp+W2a1OKjv8/S0Or7h/8x7fAH29l/phUJ7SLCQQiTqtA9j0VelqP2UaQvD0/fOddz8FjpsdJG1vYEq/iq7sZLu3bofa6aeNayYO2+9YEAT+2JD5mApIx78ixVh6TwZEIH9k7ZGAi1BO7zhA6dD7Brhvc4vXc5Y0GPuEvivVLqdy+ZFDhkvwgHgxzS27eSTeWICve+4ohhqA3iif9WK2WsqUT5Zfe71Y49tH2acpJl+c2uVomXYelOA0yu4m6/uF9VRJG3V09f9Wl7HoGV9inv3s537a2lUq7Zb1o1dqx23/wAn87iQyPgkTv98btqVfhid93aCbOXcy/EfCEfv3cU8viaWFkDY6d0OZ198zvRBQdFicyhBD/ho5tnTlpktwgH8fEJYmgWm3Q9Sdwxwj/+m2OGkjaQf3w/raBlN3hv2T/Vj7SUrj1ymH4ywCdlZapx8JsPq74IKXh0/Lz5J09oVOJXrG9cfUmb8g6ax9UP1O6rDkznqT3xIRDwha7/Y++MO0iRydHx8R8sPMkkbyjikhIfj7f5UVfp+m9UlbfjTy+Rbig17v9i6rQdtopwMMghzRqVYOqmrcezrWvZGsT4cardD9//smp5cuGkI8ceSt4X2oZLEsKUIvTs7aek7Ed3gmvnfLShZRUo82hLSdcRAyrO682vd5RP/b7aFYHAcUoVl8tyZ/P375Vk5FVVpB0fv7JKYd6wGh+JKSUSfxdI5xFD+vXsxhfuKKF3cl31/Imz+TzLLulXDXJISwepoXV+2f9qrGvZf+Qf3aQyhre+o1KoVvS0HHpMrTxrGXxSVjwZB0f8dlhGmXI48PyaQyk/ujNkmgv6XXxx777naRzUKj60rzYQWKp1FOVpBHyhga9ckOaPFEmRJ/2G58Hg3ip1dpRc2eOTeaK6cwYM6d+P31CSFY/4hTt4aP2nU9ZGXjBrhwgH8XEl48m5vb5PThFHCjzzM0cOi7HAFZkDO7zzosxCzZLfBH+teUzzACIcNNFkHvjt3WelF9Yt+eAF1Z/d6YKR/dYXn9/3gouIgXehfbUbAgGe2hOf3AS84f/9aetUhxTysVV/eVVjcpSi0Stxl1TSa8Cggf14RDhlmqTU71k6afpXtpgmGeSQdnRNYemanRcedOhQF16WPjDljjfSi3LsP8JCz+QQyTyMaVImE/WSLu9lvM1362uffElaUjurb68L+w9U169Zeqy2dkEgoHkYB2IEvOHTpl8c24n+5c7p2NP/3s78wZRirR0v478u2ve65NIq/oNfkQnTpPCxzbMmLbBBhINBDukg8XeWlgXsVv7vO+3WY8H+rr4gTXDdJw+nlYjsPsDY8yJyKTLwSSk4tHYe/EWX1ENHZr36aVNqkcBerx69q6oqBASTRWprqwOBDckl2M4kUNJ037MpL0/k8d+BX3E3If6RPDJffz2z56ARg/nSXZgRYsEbD6ycOq3a6ulXDXJIDcT7o+IWsbbkBzdbu3/59m7buak1leumpRaI7z2Qh0vikeB4XjYX4pmXlaWI1L44YU1KgejOKT0rLxpcRQzXr6+NRDgcE23DjXL8DtG8YckLdvym0e/+vtcbcTGED39OlrHSbhcMGXER924hj0e4rlxXM3/SrHpLL90Z5JBoiIWJWl7w06st38W8OljLf44lfY6/d0/SHnUT0yQqMRH5yyd0TBYLr/3Ha/zSk+ena2XPqqp+xMqHamtnTF9CrOQa8cibYi9bmBzyLXu2PfEvb1g7kkGLjcST3THWoceA4UMqiBEOoUPrP5vMf6dYNsIBDknL6nmVzx+eVzWrV6pL/bn8dD6rdSljhE9KwaHHziu3+5PUhOf+7cOkXfpmaWXl+VVVqb9DcmoJ1dZuDAR25pRzp0BJ079vT8r2GPKtemQ6dXoUIyfxDHfMe1bfS0cO4KH+lKU7pWHP0smfHeTTJIUHSVjuY4xDGvi55QZqTodWDDCnHZNbSZ3wHqE+Q6nWW7gkNSr5l7U/lPxVrt903X6x++RZWuzcs7L/4KosAmqHjtfuWxQI8KslPmkEvOF2xxJvipU9yubLjgc9+ZOK+qQ25148bBifyiphb7L905pO2w0f2zpr4gKFebzh/JtP06nXrjHJVamZSPQaTdH18HhMp3+C/n/qMcQXokqep6kajfSrWsDGJV+P5I9e360lKF5+4MCC+ZV9qqrOFa/CWLt2PXpeXRMIrKNUcoWsN3wrS7wpNlTy/p8PlURuB+X7ieQRUurWrv2sV9WIwaf7CNMkb4eBF3571bSp22XGq6X+2sy3N3rVSz6N9dLJ2LVT9NNlK027nBjuPnR+sg10jdtAhEMy2gK2e76ZPDdfNG57AbpSqp5SWXlRVRXxF2ZD7b6VgcjLS/FJInBmoG9sxY6HNqwZftQTuRVU2Cc6TSrpdv7Q4RfzODJKhINSV7Ng0iz+JhFr5XAwxiF9653CMNu29qFOtu26dsev+iT52A2Tk/cK3sbSXcEIuYJOtz6bUNO06JmJib3Ct7r0rBxUlR72n0vt4X21MwOLckm55ziPafj+3+IhDWHv54/PUM8UREYSdWvte/QfMYRPZUk5HEKHN3w2eZW1IhyMcUj3vEzG6owKjWXOGEfyKG5+L2lvc8+kHZ024ZMKBjnwf25I6Fj58GL+w1fPT0k0wuF0mspw7b5N0wM7aJUcKy0p3V+4MjFB2nnbwiyJgogUotMkD49wGDGQJwWnRDiw+r2fT/6MZzq0TISDMQ7pR38lInWMuDE8i4rnjteTmi88wC5JWXwTLimOIq8N/7eebxevWPMH4p25eM1sG6fxCIeqKvFnXqK6TuyrXRyYzrMLuP4jKZ7bXi5rmSGFvV89+rJ+/igCtznCoeKiYcP78WSsYcLDSeHjW2dPnM+TiFsjwgFBDa7/ruQCkHT/YEPfEbmk8zqOCIe8sMUr9Rqd8Ee1L3wcL9dx4+DBhfMreQ6H7hSdbXv0qBy7MxDgD764/CMpXa4pa3kxn+JlT76mrz9izREO69ZN7zVoxKVnkCIc2g+44LbV06ZutWCEg24nzW8Ut350Q2gZRY8kmfJPhvbqgQeSmhLdnDnT0D7ZQ/m4dXFcTS/pEZSvMex2/W/9XeBYvC2xjYbqJS9+K+WhXQ3tTi6W2M01SigKTFbCL5cw4lxTiI0UUVrS/aY/LKoXM01cSj6+/p83Rn55+gm5iIT6RBWyygzp5OEjRw4fOdYgh0LBIP9f5JmtM34pPNqD/y0sKpW1aVPWqk2bNm27nU1fgBuWEpEm3KiFBZMj2ecZ2s/oPIm63DSacY90uaH9srzys6r6xvooTx9/OLat/9/jK1bMn145aFhviurSc86pHP7QrAApZxulARvIeuT2V3RrSTwXLJn7fFMBzx9pD5cH7XmUpq1bZ78zYMSQ85KTFGnXaT4ite1TedPG6ZO/CPIcDtZ7OClX93Me/2fc9ebaOPLFB08/dE1OhaoCw3MpTxyvVlWQs3DkXb/61/y9CTW5t67KqdNmAk89FR+0znfK1UH8Kt4cYWOmu+dJX5sfZ7VjqOFZJP3987BRaPeKt++rUDe5C0p9bOzqlgmSojRcxO/5GDbo6DTJ0yV5YSN+duTYOLnt3TsjkSt+Y6YpQkM2punkX9Xa3dg5Z96L2ketcGTOnEgvho4YNkzlVZyqHRQbuWpVaxa24QEHLR8zgniHzxCf9sb6xdhoNmumi6dJw/vFUOx+y/h5SPDwmbHmxP96zzqrcuB3FwcCBeePEG/TOpL8TUZjK5tX6WTPkedWRVN2G9Q9Pk3iEQ4He7NYSJ94O63OPWfMttmT5gWZ5CvWNMkYh5R0H1wLx7L35xn/3dFqnFa+gHf0hhEjhJKopCZ9o7VjSemEh73lfTM6ODe/Rka7OIfDZRe3j0GbYYaNysfEmiP9bdu2e+XYXdMDq0m1HCHsDV04sqx5CS3smTHewPlRFBf3Sb2uzesulad9//NvW/3JlC1B6+VwKORMmJFjbtj0xpWFqG+pa/ySXUonq57enWNY/PD3U6rYf+ez+JALSHJCwECwabxniQ13rtz9944WAvLJvimv2yFwJ4ie9pMEcPJWQ83Sl25z4tPjWQH62P87psgRWLLS1F0y2iHxdx79OL5ASDaRIh/f8PLXImGbRY9wyAqVcnBxVgqht4QmGzkbJFy8qnMqExL4fiKaSWOEPxXSYx+hhEPaZEanCSZVN4AL7yadPi96qeM8an9vho36TlZHL1p6eOPsXw83o6OWacPL2i9qpiMroT8ww+/yMXb6DKVJ1B5qcsED838ZyUXl9RsRDWi+YdaqDTJWtmSkTh0iXL2qdWqS3bkhNgz1v/+lV0MW0bMgNswJpnSIYNJYxzL+us0n3bM9hmDqBSYYqWRMQZe6SF/De1a8+/3zTOirRZooYXecaLaRrMzuwRfDjAtpaB6xdGVICcfOijz/1m9/7+7IzcJiRjjoZr9qbQjHHtGtFcLVq1q3Rtnjh7QHpyj/p19DVtC0OT7WP5jSHYJJ4z3L3HCXS5pc10Kg+idm2KjLk5nA6SUnti7403UmTBXMIJKzDYl92rxgF1L2P2i4N+LdafV0YROkZnuGj6z40+U8yECy/zTpgOYZuurSnOYTFiBcvaqFlQoITtQcnaI4LGdSPOT9hwJcChchWDSLDSKH3OOThu2LoXitf+EWyK2h/8pYewX+PbDmk4cvzt2e/SX8bEBTOAorqEzo3vI0kqHDqtykBAu0TnP1xj2f/jSSvdLnM3pSZygPdlKLxmt6tku4fFXr2S77sfbD6i/p2lCxlR2P2/EmU7pCsGi8Z5obLolweC72VH7TiFYmGOnUuzWBkw801ix9+dudTeh0cZsoYS82+4ewEhrmNWGG5L2zeUJGNohKBfnExle/EXnoxdYRDioDixTJ4vkSRE4hwuWrWkSfuMxlX2qMUHlLXIkNJGN3y5UmUzpLMKgW/5RyN0yT2tS3GClszm+hyjdTEBe6c2TjnN8Ykx/RlDNWpBEvK2tovqPTpLzGTAiDZB3e12PFLm7a4MEFvx7ER2rjCIf4WFI2Gr8nYj9xGcL1q1pcq5hkIvosZYjKRLHqNpGKja3anP4SDBrrWa6/jvdJ340R2GfKdd0zVHs5PtYT2l95zxfvPdDDnBOsKK342V18whLmvxvkpsHcIRm/+DX4WMEhDWk2rK9+/56zOD2fMc+tJtnFxKi+4H26vPs6qfNF3Bz7pnrjjnow9rlYYrmd6oO1QelonuuOJ7tz7qdscnM8/tFZeT5STENTPvo0WoWc0tKZF1/9yOt/ucGM9cacnTFCIMhOWb6LeSSZhT9cIjWxgt8Sm6uTJWPahXS+rped87Vnpv7lSn8oJNlx6U71l27o3lwgqcdVm0lz7S271VTdueVfUW1pUe6KdpJ47rnn+DA1nK/eAyHYU5W9ZqGjp0kDH3p5Lo9rWPwNvc2hqu/COZqUCzpwYO1nPzclJkN1VEYX9r7vtVX8fuyX1zC/0U1x/V0/1ymkIc2iTXum/yySVtfQCAdDpmCqmYMee9kEW5jYxD3eO1VaS2TaUTlov6KHIl1+0L4TpGbi0bxCl9uPvlCPly07jb9gvMfcWULSBQq17m7QwuBpp1X2/ubaQKC2wA5asbpH3rjx7QHDh/SZMpe/ztXwj2fAQEokn6KIzqb8Z55x2fcXTwoc4REOsgkD0Y/ULWmuNbJrwK9swi/qav0Gl9A0T2WYWxKHHbP13DWmDGU4wZ4q5HMVOXqa1OcGc6YXFc/nwlzI8SNfzv3fUaaca+Y2Inkj1/xzrj0/r/xy1L62e4kY0hAOxYOXclsvdHDhbyKJdjx2ejjprsxxraJiFZAnXMCqBdTRRbZljnMvXQtqNBMgmJNzP5DH2/yc7JOMv1UesVLVlsxTXrvkyIxYlj1tmdQj8t6V7z9Y6cBvhCeyFGVCEjveygW7CXns5Ia5kSiVUPO7A1ONobXXUPPhfV14Q4ZEOJi0ZHdY5wA7a5yyd07JeCuFw5bsrMFZrRd17EEWi7lQO65W5uS3VBh+qzwCtNPg7mpcNcoalv5X5SVVVZR8DNIZZ1Recsfy6YGTGjrtWizLzCsrxgc0cDcx8qyWV6ULsJI98+8aOmT4hT6mhD2iS3el3bpc/qO5k+Y08rdU2GPp7tF03yqPE4BDFiH8pK4mKxeqcFvGDwtbLa0KjdEsIYI1+elVHenWA/m89NzJ0ySjbdUnW5KS9C+9cpD/Cj1nzA/+lSP9Y0Y95eC6wGMDjR6LU/WXTyes2IWUO5mvw6U/eCcylQ1Rlu6a9gYe6cMZ+vzmzM0LMtcT6efYUwWp06pMuIRVa+kosPzX6SM15YdqgZ22ZnWCNTn06pZB5OOSeF4hayKweq9KrmjION+1C+SaaBKGVhfe/KupB7XFVI807fz8X3fk8R5AqxM0vn/S5UHxh5BkZdepkQAI3znX/mZOJC1LKKxqDtVCuW7T69/qwEekayC4IUt26etW6x423hDFaeGXN/HXEeNTPAIvRJqmL91xj+TUqDsDbVE+hrL8Vjf5QKQv9atXL5hROWBw5G0Gwh9/ly49L/3e/AB+OQgjaxEsu8Yn/qpY2Tv5qD/oYaGamnkTLhk+tLeXyYpHcMojta4877rNMyYtDjKPt1gvmBXD849UjyobFKVF+E1dLdZxutRV6T8p9HnVE70jdq9BMCY/u6pThouluxQchu30X5H6xc6+t29MoiNSz+sfmVCTXT7z6L6VH/6gV0IJtgQI9NhIeAgpHBoWfTJKijqhM0b9fHIeEQ4ff78b75chEQ4C4xUSGZ96br0iVIkuRLiGVdO1C9ZIfz52lGA9iKUSIBiTn13VqZVxNymNhyG7p96Z+r3Ovte4MLUT7Qd958nZmlmXNXSd3Lbo719TfawxVTn2Wgh4byfkVQ0rn0dC/6IfKRLSUNbzlmeWRV53FUz/na1hn0hx+OjqZ68u47V1Xbpr7pVO/36U0v1jOmnNUEO4hlVnVNatoDZlsMp1uil2lSKCLTnv6upMOJgmZTLRt6RH2g/N1BM/fe/QzzNa73blg6+uT5fLtX9w3YzHI6k98REh0GECKaTh4eRkr9FpUseqB9+KTGVJDyc17Zv5aD/ePa9FIxwCKSeZMRENfPiEi1i1iDHzk0l7HuZb+Wlxey2CLfnJVa2OCxEO6lz0KZWGpP32SvmWZ+zsVHucqOyCb/xyCjU9a3Dnsn/fFUntiU9OAlVHxEMaFPlQV/762qRPdJrk7XbNr2dFXrBDi3DYPP62TlxVodOklP4kda2gzZQMo0ccG9HQzOiF24cmw2qTvINtUwkgwsFI3OWjygnqT87brCLdsGZNJMKhijTl8XXpUjn4vgWBgIpCFKUQKLny1JDwJV32zNjpCyXXVxSeSyK8Y8e89y4ZNqwPLcKhx7nXbJk5aWGhEQ7CvU/ud67tlEVfB6X4Vh/331McUoozVq+A0gwCw+dmFGUpqKnQOhh1SdSou9GMIepOi2iivDwpSCFRqrVV95HGkdra+fN79q4afI7GcdXiU06prLymOhDYoHoUhTEC5TcRnr1V2PjMXEYykyTlxJo1n/YeNLKK/wIJC+fF83asumjcyqnTamQ+7Qrn+/yLYIhfbMBif7edm5ALliS2dd4iXMVqKnRuO1nd5h5Je48+mbSDTUECBFNyjTUVWdU+QA8E5/pmIRA8K9XWYz/Mejz1YHjzRU2pJSl7p1ZWXlxVRfzxVl9buyIQMOyWdEoH7bkj3fAxU0Qv6Yq0qV/II6uNVOLvymCl3S4YOvwifvkOCedwYEyuq5k/aVZ9/ulXDZkhJS9bTVIbsLPKXvld0niSx55UjM1sBIZnO0g+ltc0ifEXJ+HhpCysqROkbP6IHV22bH7PyqqqyJ1w4U+riorKUT+cEVgiXMNtgm2uZ5SHkD4IlahbKbJ0pzRu3jyrx4ARl1X4CA8nedqd3+sb6z+bvCbIvJ5QHtMkUXdKMm1d0k+fGyaTqlKECT+rayooiqmyx9olajzt8FtmiZHquEWwJG+1pkKk6bzmSbPgk7TYVr2RvBCgJRUr3/P1pbFNzb+llZXnVw2OpnPQlMk4EKqt3RAI7MooRwEncP4nZxPy2DUOXuMPanOLTpO8Z/W9bMQAnrIzHA140JZOPqI07Fk6+bODfJqkpNyiSpYxdTsp4maTgQ0TIrOqDewGY68lDfg5Q1tyqHKCJTlqUWMiEFzH06XTD5JO8pyb9dPEmi4fevffluTUliZwbPO8P4wx5Je0WKctK+V7iJDnO6wEMu8gpQ0tulbX5vzbX1jLTSBTUt2FDi39wzBuI/JbKgxZsksa1sSkbcduTr8rMbSkyWGiEFtZCRgxQeINRpfuJOIvhNGIcFC1VeexqsUahZohDWny+/cviEY4VKSVZ91t165Hz6t3BKavzyrlwoMdbmIyz0wn9lHYm8ynvmIXVxCNcKhbu/azXlUjLi3nUXeS6O8Ab4dBF35n1dRp2wuKcIh3pMCNpF80IwpUla064Xd1dTY9hR9LegB9QuHaXKeBYEh+alXT+Pz0v5JOR9FNpF9Ng+wfnXSO56Qo15yeVj/b7ikD73p2KUV9pP366sUv3NI+m1rXHZNGNYo/hCQru9uLBdBF1+pKe9z2zw1Bzp3wLj9FPrb2H9dHfqETHk4yYoaUFAa9gRTOa9tTaF7i5yOCGixmxT+xNmWt7id2ChEOacDKx7ZKK8m2Wze1NtvhtGPHli2bN/DSC3ufnVaedbfsnHN6jvjBzMCirFKuOlh2TQklpGHKkWx3kBLkmiMctmyZNejyob1PEZ0iRepL7fr1+tqG6ZNX5RvhkOhEQVtXJX5B/akgRTkqE35YV+dQVeDhhxMjnlOgKhdWJ9iRc67Oh9C/P/g0YSLRLbw5KYH6kmWi1CJy+65K1BTcKhv9q8+2UKdJoV3L37ynm2ALjhfrvp6SVzU8MppXVZBKdJrkH/Q/8w7LoUbKLElRTm5963Zi5Ipgp0TFbk6cu98QrZOPHOFCVp2PfkKdxIiXEWpBNEqAYEfOuTo/ap8u2JkwkugWXFIL7FPuEEUWkWtanJeNejw06yilmajssc3z/9gzr+acVskzjrCeJiv8QkWZ7fD4hMjtqbPum82xU3KvcvHQ4aV/Oa+IuBMnb52hvSBcyKoN7Qhj6+NfJDxLTkVNMCOnXJ2/KeM2omzQf+tTx28H+R6vU5gdfizfMd0yk9JOi+zqq/NtzlH12r9Dyqv68+S8qmIgJF8kJfg1izl32iRJVvaJ2siIe0iJzEGuWeBd3idmUkTZxUgY9Lcib72jKs79JbXyj0k3Nqja7SIvlSdukgr0+QQlp0OKvvc3j752EDVUYfvhFB1u3akcmzOMO4HGc+QdxrMx0D78qSKvJzht/c23XFImHnDH2wj71lYzSegx2YjL0/vjQof0RZwhghriKKy2Medf7PUFxE61eYVYwZHi5SMoUXMnF3yZLwVl1fg/v7W+nlZ9zTaavDOlS65oHxKO+ZalmTXefB5aDQc9vpoXHnt1n0cipKvzsc+L+Sjzr+LT7psNtT1hrafa0I4wNio+5JMGt+Q49QQrcsgFG3Jv3FJCG3kvPjnKTufPEILVIrT/tsIGP/Y9SmvKl3cX1pxDap+9iLRi93X6il0MVOTW05CJBBuFld23EW9YxdrS5e9Tsb6S54S05gmXsmqaZrr0idiYhealdP3OrUGwImdcXSiIoY9PiZsq98bThTbniPqtbsxNKiER+rKswFFXPPJ5Q0Jfrq2JgwtszhHVpesJN3ZkZbOfsL6XDsjDb/S0eexLpSmUyzbNx8PKzL5izzzx0In0xnTYj69abdFBmU1UrLZJPy3XTX3zquYe3oL/Y4R80bgjGCFKzavakNsMWSWq//XsJuEfs/XbV2ZV5pKDkbyqwlFzMvswWCJMOIOgHJL8dc/+6kvB510VT2jNJtE7VoY6pFUZQ3FswQrHjszogc2lNFBTQZFWl73u1BvVD6iUxn9bqRxzTxEtpKEu75CGONH9r43889b4XvaN6tWN2QXccbTbtYTJhdTwBuG9SSoAlaB0/K2Lnt3PgkIrQgeWhrxCgsbMkOJBDS662ZiIahiiYj8UWYrApKeWivXngzvF5Jwt1XEg5UGfxjX5PYWUyvDIK//amVqitbdX0JZa9Z1R7hvRVTyNnexZtErKkudbBIniKW188k9H/QKzMontFA+3NmKGFHdIgqeUyPitLpN4/Ag/qim2Miivao4uPPKjHAIth2HLCAjaBOmE1qtixZC3SCnrfvPgTJGpz9Eta0iKHSrM86qGhYemsLcoWRrU9cqNbMfvb1nC84urH08qDa3aJon2zgiHFP8au8gh8XfJt3zio48V4K/1CCx9Zo9Ap+aLPs0noMu+Iv7TKe8uV0QTfecEMv8f/GXYOT9fzc8p4gIBqe9o0agBTsO7732C+9LG5/PO+u02X+450skAf6m54MdQh/SxYCecILY9Ngg4pBgJK//92dn35+4eQhoijMrHUk7puk/25gYrJHH03Rum5n4i6URASJnDhUqvLg0KX8rDbOohv+iMJRu4UDg8aeS83OEKewK5ZWLtCI8iVkHgb+z8jU8aBOrYXmRzbASx0cf28TcLgeKs2EU79GKWbrUcgikjIDpTJkhMtwkSb7n6xZzLcccX6uX/Wmxuzz9n3UB4zkeSxxOkswLxlOz71XpP9idsw2zeIZ+w/zPCIcXuIYmsimQdrp0OxkPc8bPaJma7a2OOju7qnUPAFYfb9RtEGGdwxzSCdA7RpklPrMl+sWPBqTl0uOKwZ3A/RXhRTPGsmsV0mizITeGZP9iXvWmFTSD4PyMdkotuITEGh5THV584QcqjhSxVXo/nH9QQwk+LCBjqQ0gaMPMrnvJEfOVBVYF8eJJqucsK293IcjjuJCAye5eV5I5ESKqRbdPjn33PPv7KJM1P2FczndA7IxxSbKXDnQ4pNnpNC+FAvgQq8q2oUe9w9qycsGSEGy3GToeHkFKMtWBC9ttIhT/zlNKcTXd6kPKqHs0jr6omGDnIZr8kaXokhfui91lpFoeVptkIhxQLu3CVQ/okBhaXsRgJy//tmD1Cq9AMOJYfv0gHy4efKSLWIlO/MPH8A6GatujeX76VLTuk523tqu454r+iIyWv6qzteeVV1eIp1f/3G57YNT9dSOLxdS+LhzQw8XC89Jay7D/fcmx2FhnnHXqm5R3PyNkgbFviil2FsGJRwRvFf7mJqnSaHG2CpM9DSCkMX+hzqdbVjrFFy1NkXbrT+SZC3gWFvcG8wjEGAkSVkqbfXtxPSzDoX7Heq9MdK602rFJOSMtZbZU+ox9JBAgG5FkajbDhj49pp4dM6qh7N1vxnJ3in9Bm/e+7tX8ky4vNf+5eyyRGLl1Lyqu6pYSQZCjRSpYtD/upZqbxJuVnrKzIQQ1Zuo5DIBAnMDy+VbSNz7MEDQ8rWq8s1DBtglT3Ubb1tfyGdWTCDM2MDfLa0vyUOqpWa1pe1Y+aCsirqgpOZs/P8qsvNih+ZTNrJEzgjLiHpNppFIJAOoG56QXZ9msqsh3N89iiXtM1a+JmIEdDjLEzIsag+rHdWjaaU6vpq7SqOLC823WEKY/UWGBeVTWA3oZ7j6mvq4bZkrUEd2RMclW1LqMMBOxF4OZP7dVfQ3rbYQDlWazGdQuN6MXuKVr3IBbVGtGezXT6hnej5FVd/EWheVUz+YRLt7+nHrkgsbkHCQt2cEiZcFFiEoGihzREx3lAa7T63w3RasnC5cQJki55VTNwHPlMY4pUu2ZXhrD7Ctqbnlc1k3Ej++dhj8qinew9uvQYZkiZwFACAuoExr2qXv6fcEg8Bvf0sep01Ev1TBuU3MKsRepZVpe76sGSZCLJ230up+RVrX1Pl7yqyR1gfAokLZ6hNhFS2MovCeuJXCvuIaWixZ7bCNzzuuqI2wjkulOt6KTC8jGxNGAiozqhNZMRqZxNpu7tatXD6+LpUVQPu6Ow7OqykPBVPMymfaVLXtVUtgr3Iy/Wq8yQvGxFDWmCBIeUShZ7phGwxoodH676S/gQ0sDREGPsjAhpiJ6Pi1TfaL51M24hMXam+PuPOUtFt7yqUcPE/wmXTl+fGdYgs9qVxyUVRxWvl7Eh7FszaqIABBxBQDVdw98ed8TYChtEuz5VBAXBXVMI0iTRI/PVLmqb15OUOFPYU3W+eHYDxbt6hl55VdNwBtkHaSXR3S0riXMeOCQ1jCgznABxgmRgf4ZvV1GOO0gcCnGCZExIQ8Q4wSWHMm3UuANJURjjeVW1YhAzkck88bZ+eVWT9Usym8Sakkv4tuIJr9ugHn2XJpnYhUNKsMCWdQlUGNe1YZ1UdGPFjkOxRIxd1Djb1mUmu6n5InveVRWrOrCo+1WEKYjn2FtE/yBKTGH+rSsyfd2hJUGv2uRWWy0ckjYbHHEFgfn3Zw5z0rczy1xX0nno2YQx1y9eS5Amiu5ReSisdjFRiRPF/Zd3CntFByZLs7fpmlc1ueHgyffT4+wktntesojINhySCCXI6E2AuGJXoXf7yfrezvz1jRU7DsgyK3aMNaytTrZYZPvYtpXpRS7cP+0mwpQnmlfVKEgSW3gy/YsUXr2ZGmQOh2SUgaDXNgQyfmIuvtI2fTeuo2XnUN5dLh8z7hYSH+OqjGdjD88xbui20SxdPIwS0rB9IuFVeUQIin/OprTlOaXxM+YnqoFDIgKDuPMIrEofEu4gcSK0CdKJj06kU9Rz/1hGVEO9dhZCPRu2tq7W17FgZrS1Rp9l9lGDX/0RY40apOIg25cmL9V+Spi/NVeGQ0qDiF0zCFhpxY6xR9O/pVix4ycBMaTBsIeQms/HNWn3xusWIm0QY12vS79vk+XbKzW9keVowYd8yuepz8CGeR47X/oqXq5m4JByEcJxxxO4Ne1bsK+H44ece4Ad+vfNLRSXaNyg+jhX/HihG0f3piUdDE8uVKUD6nuHVcg+0XHIniXL9c+rmmg9xLalxn0r7F1CBGBCkW23CO93q7btIB3ZcYLl+NvhjDdebeo76I45EjpxUL0mpELJvvfVj4jqqeLdjqR0QMb8iBPsNEnzxXgptKI7IeVBVkLFTpD3sA6KnNRsSOGJNNJ+6uVWR66QWyUkQMBmBH6Z2l/cQuJ5VWm3kIzKqxo3TOfV8c3IhvReyq5Ld/pcQcmrut+IvKoJ8rKn45eJ+1kKD5+YwErTF8MT4hpbcEgaYFDsIgK3p441I+ou9bAr9sqvPIUwzrrAToJ0PqKrToRSqhl6OySlJevulF7VipJX9ZMD5Ds6pLErW/clYhgkHv33XGJXWBEckjAqCOpFwFohDXxUf9drZM7R05n24gmDQxoY67An5WbJF6kTJudwp4yEnFfV2Ku90npP0hJdyLtxvVc8q1Fs3MZ2MdYK/oKAlQm8ldK5wSl77txp2/tSwsCDuycRpPMSPXEiZfVn9ml5aXFUJc+gC8VX7BTv2umErHf5gCo5eSDpMViFzSxTCDGALS3CIeWDHnUKITCcVLmGJJ2fcOp7dRD0TX0IyfA7SIzVt00J4ZqX8VxSfpa3c622PK9q4qZNjpEYl1c13nAT65hwQIqffdoop8aBxyWzbMAhZYGDQ8YQmEtSW0GSzkv4lZRaiGkgP4RkaJaGqHHabC5LMtLcvUisymh5VY8blVc1bhY/W5VYsguz5ZvSHh2LC2bbgEPKRgfH3EEg5eVH9xj2Wh/7wOw8tCuhs/VLjb+jU9cqeYa0dC+hew4V9Y/uTMmrOmeLYXlVWwArrFXiDRQeNm9fYr4kbgI4JHFWkNSFgOVCGljqu8WwYmfBCRKTWiVF2R1Ya8ZCri5nu3FKrJNXtWWMIW+bcOxBJ9lzfNkR+oJdHg8uGQcYmkGgSASQFi0VfFk3SoydfML4FTvWvinph8JK+CMmXTickle1+mPj8qq2nDz+sOyNRZ4obM2GxPpd6tmVdQ8zpKx4cNAVBP6ZNMonnk3acelm+Rjhm+WcUN1HJqS2ONwlKSvahk0uNUzSsFtdJ1FCGibWG5hXNdatrvEoOy9buTVWSvoLh0TCBeGCCVhwxY4lv0YMIQ2MWe0hJH7StTs7ceZVb9qT2HHrFi2vanC84ZykYOszYnM2mR1ceZS/1pz+gUOiM0MNpxFIWrJ7/mGnDY4+nvaX9CNUatw4lyCdr+jpRxP5M7auyVeLc+p5h51Hyau69HOjV+wkxVMWjPGV2LYVea3Y5Vcp1iz+ggCVgBUnSOyPiVEk3alIFLpsy2Jp7KL0t3SKG6Fp57L4tms32t8YXx7LzUBhb7OSfIKwc6uOSyjMe6hDLFeQJK9fE9uOSwhtYIYkhAlCjiawITE6rNgxL/FNSCaENDBW0T1uo50rTsa3XbvR+0rxLA3Me2ACwX3lydQTPLOn0uxPFHZkSVPa62MFtcIhCYKCmHMJ/Ht5fGzTvhnfdO1G+ZXtCWOvm2lKyNslx+N9OrAwvunajdKxrSl5VT+rNTavasQOEruoQWoOhpHYvjn5PITEtcAhufacLsrALbli90Ui2zcmSOSHkAzPqxo9UTvEl+xOVCd+PxTlHLZCo2fcSOrFv0240IdZ5zaxJ4+UtRvyvGcFh0QyLISdSGBFfFDL4ZBY255D4jxyb4T2fpxbqHCJdm3PiCk5Oiu25d6/noEXi6/YKd51nxqcVzViCR/rcKrcPEOSQ58wf37WgUPKjxtq5UWAllc1rybyqJR4G3abgXlUd1gVK4Y0sOOV8ceQGj91GPA8hmO1vKqRIXhY79iNKs+BqfmFNGDJLo+TAVUKIDCXUremgiKdv2wiExti7PhDSGMoJE1I9B3pjufiWJBYw0JT7llRGJgve+7VhDU4zwnD86pyAlKTNzZrC7F5ed+zwgzJ/LMJLVqMQHzJrv4ci/WsCN05bQgFQv3nK03p44Cm2Pv55ImmNGjpRvyXl1Pyqs7bZHReVU5LYpX+Fi+psLcI/jKVNBxSKg/sGUnAkiEN7N4fGDlmu+m2Ysw3Yx3jMQ11E+xGVP/+drqJsCKmsDfE7zfl31eZdWzf3Kuw/0j+ifPgkPI3AWo6g0DiKaRWzhhQIaMo7UrKq2rSil2J/6LYoN6Jbbj3LzGv6o6P8ox4IxH2sPY9IqHeCm/sHVaaT9qgSHtwSCTqEHYggYVJGU8cODzakMrHJFL05K5Z9/GR3EI6SDT1jF/g3tBBnc1VtLrWQ8qrWmdCXlUeVVfJmrhDkni43d8IE7g0W8AhpQHBrnEErLlix77MM0LVOFBF1EyMsTPnISTGRsfehrRmXRHhWKTpLtcTnjqVTMirGuESZNc0T2/C3i3rvPHfeFRkcEhUYpB3GoHNsQGNpTyAE6vkrL/tL7qAMKCmTbMJ0gWI9j6tpKX2nA4FqHFGVe/Q7pS8qsuWmLFi55W7nd2c61tms9vF57Nk4nBIZGSokCcB4gQpz1bI1f58XbwKctIQJ0impLHj5ulXFrPRgoOxLdf+PdVqeVUjllBYv+Y8DYqfTa+LxejTbQSHRGeGGqYQqDClFca2xNtBmgYv7SEkM14VG7GO1KmixUgLdyOxai9SXtWvTMiryo0js7Oac2nIbNXGloQNLTYj/YFDIuGCsPMIxB3S/Wb93rcuw85XdCR0rm72doJ0AaIdz27fUnvZ7gLUOKNq6di2pLyqe43PqxqJZJDObRVuThy0sBAbwSE54yy1wSiIK3YVZg1pWqwhpGlgxIeQzApp+Kpfi42+WrstZi3X/j2dlld1vBmR1AqTlP7cIjJTvHXLvorlWM3DRnBIeUBDFScReCY2GDikNj2HxWAI/A3VmjWlbF2/qnmlbrVJUzKB0RdLxDOwv/hzrop3/TQzQhp4kF1Z/Y4w931htn5dIS4wlpCjWHjRrlsIWDOvKqf/M/447IP87+9+5xZTaI6TOEH6KP9715pdUD1w8olLB/XqWcHYxo2qx91U2OYGFhR+TkH2vq+UNJmBR2r4j6pRA3p28rFVmwppDw6pEHqoSyAwlyDLaioo0oXJPhSt/iBCGphFY+wY27z5naqqi3u23ryrMFM7oDYtr2rdm/k/o0qCpbCdOz+6YPiQga3XHJbyj/pujhwntQxhEHAcgYfYc3e97rhRUQd02qUVhCoNK+JJaQm18hVtmj//7KryxflWd0w93+gzCHlVPfM3ekImjd3LwitXvjG4MsA88VeFmNS0RZoZrgh/qi3SZfd2g2AsblXYqxhnSt8pwl8oLnjwHvP7iFvep89UmoStFFLuYLEnik0wluSN2EcipJHI7BSW7DKZoAQE3Eig9OwxhGHLZj2ElNynAtaCktXYd1u6YAQlpGHnh7F35pkxZIVHNUh8dlTIrUX85DDDUmgDBKxPoPNY4ZvlfDB1kw5Zf0iO62HZtd6g8DVbZpNO+M1dPpPDBbkjZPt23Blr0QFZ9SEki+IqSreoMXZF6aTLG6XlVQ29YTtcwt7WdiNDh0EABAgETr0o/s4hgVpNW2YISEFEXwLeIZWK8F0W2bN8oTkPIek4SDgkHWFClRYB4gRJSw3KDSSACZKBcHVSfcqNBA+j8BfllRRyP0enTpPUwCGRcEHYFAIVprSCRpIJeCz7EFJyL12+3WuMeEgD8x56x6SHkHS0ChySjjChCgRsS6B8dCdC30/O2UqQhqg+BErGtBPPqyqz6Xt8Zj2EpM/4uBY4JN1QQpEmAeKKXYWmIhwwjABtxe6EWXlVDRuvHRWT8qoqzJS8qjpzhEPSGSjUgYAdCbTpMYLQ7dABs/KqEjrleFHPgIHiK3aKd+NUwg0nq8CDQ7KKJRzcj+EOHptThkZ7M1/dR+Y+3uIUyoWNI5JXtfmVQwJ6ZPa+XGK/B4nhkARsC5ECCcyl1K+poEhDVh8CCGnQh6ORWiquIdxikU6+WeAzqkYORVM3HJImGhwAAdcQ6DT4PMJYG1YuI0hDVB8CvlFnUvKqLljvCerTsJla4JDMpO3OthDSYH27EydICGkogkk73kSI4lbYG7Z8lQMcUhHOLDQJAtYiUHIWJa+qUoeQBvPtJ50/khLSsNvUvKq64YBD0g0lFIGAXQmUjy0ldL1u8kGCNET1IVB2rS8ofLmW2eRjJudV1WeUwiPUpzlocR8BrNhZ3+bEh5AwQSqCSc++nvCiISk8vghd1KFJOCQdIEIFCNiawKkXXELof9O26QRpiOpDwHtZL0pe1RXzbfgQEicFh6TP6QItWgSIEyQtNSg3kABtgoQ7SAaaQlO18/OqRocOh6R5BuBAMQhUFKNRl7cpdR5LIQCHRKGll2zlWPGQBuY5bMO8qlFScEh6nTDQAwI2JVA+qjOh5yfnbSZIQ1QfAiVjTiHkVZUCu+yXVzUKCg5Jn/MFWjQIEFfsKjTUoNhAAngIyUC4Oqkuv5GQd8GeeVWjpOCQdDphoAYEbEqgdfeRhJ6HDyLGjoBLJ1Gpf5X4c66Kd9MUe4Y0IKhBp/MFajQIIK+qBhgLFdMmSCc+smFCGgvRzq8rxLyqH4RtmFc1SgYzpPxOENQSJDBXUC4qVlNBkYasPgQQY6cPRyO10PKq1r9BWN8zstt03XBIdGaoAQIOItCpqgdhNA2rlxKkIaoPAd/Isyl5VReutWNe1SgqOCR9zhhoUSWAkAZVLJYqJE6QkFe1CNYj5lV9U/x+UxEGk7VJOKSseHAQBBxOwH8m5SEk5FUtxukg9Rsl/hCS4t3zAbPt+xPhkIpxgqFNELAKgfIxZYSu1E3dT5CGOxM2DgAAJU9JREFUqD4Eyq7xB4Wv1DKbcsSWeVWjrISHqQ9ZaHEVAazYWd/ctBg7ZGkohkXPusENeVWjZOGQinGCoU0QsAiBU87vT+hJcPunBGmI6kPAc2lvSl7VlXPt+hASxwWHpM85Ay0qBIgTJBUNKDKaAG2CdAIPxRptEBX9LsmrGh05HJLKCYCiohCoKEqr7m5UIsbYwSEV4XzheVXFr9OeI3bNqxolKz7QIhgCTYIACBhKoHzE6QT9Jxd8SZCGqD4ESq5sH/KKqpKlGTu8IVFp68nBIVnPJk7pEXHFrsIp47bTOGgrdnV4CKkIxu18EyHvgsLeEI8QL8JgcjUJh5SLEI6DgGMJtD53NGFs4UNYsSPg0klU6j9Y/DlXxbt5so1DGhDUoNNJAzWZBJBXNZOJ1Uqob+ZrtNoAXNCfNtexoCQ6Tpl9GLRrXtXoGDFDEjU15KgE5lIq1FRQpCGrDwGENOjD0Ugt51xHCGmQGuybVzUKEQ7JyHMJukHAygQ6DupJ6F7DmsUEaYjqQ8A3oossHtLgWbRasvXrQeCQ9DltoCWdAEIa0olYb584QUJIQxFM2OEmQmI6hb3J/EXopH5NwiHpxxKaQMBWBPxnIK+q1Q0m9R0tHjWnePe+T3BfVhw7HJIVrYI+gYAJBMrHtCa0UvfJPoI0RPUhUHpNSVD4Ii2zqYftm1c1Ckx4rPrghRa3EMCKnfUtTXwICTHfRTApLa+qPL4IXdS1STgkXXFCGQjYhsApfQcS+hrcMY0gDVF9CHgG9xXPq6p4Vs229UNInBkckj4nDrSkEiBOkFIrY88UAsSHkBDSYIpVUhsh5VWV2busRElVYLc9OCS7WcyR/a1w5KgsPihijB1W7Ipgzx5XEeYMnqNvM7kIndSzSTgkPWlCFwjYhkD5iDMJfT25cANBGqL6ECi5ogMlr+qsajvnVY0ig0PS58yBlhQCxBW7ipTK2DGFACZIpmAuqJHTaHlVx4tHiBfULQMrwyEZCBeqQcCyBFqdewWhb+EjuIVEwKWTqHTJZZS8qlsn2T2kAUENOp05UJNCAHlVU3BYcoc6Qaq35Cic3anWxLyqTbbOqxq1JWZIzj6lizS6uZR2ayoo0pDVhwAeQtKHo5FaaHlVG98kvDfJyG4XohsOqRB6qAsCNiXQcUAvQs8b1y0kSENUHwK+4d0oeVUXf2HvvKpRaHBI+pw70JJEACENSTAsuomHkCxqmKRutXdXXtXoyOGQkk4AbIKASwj4Th9DGKlSh4eQCLj0EqXkVWXeWrvnVY1ig0PS6+yBHhCwD4HysW0Jna37dA9BGqL6ECi7uiwkfH0Os6lf2TyvapSa8ID1YQwtLiCAFTvrG5kaY2f9ETmvh2feQBmTMp4Jv+icotdkWTgkk4GjORAoPoF2faoInQjumkKQhqg+BDxV51MeQlo9k9n6VbEt0OCQ9Dl7oCVOgDhBitfDhnkEiDHfeCjWPNPEW2p3I8HDOCGvanTkcEjxEwAbRSFQUZRWXd4oVuysfwJ0J+VVPWb/vKpRk8AhWf/MRA9BQF8C5cPOJiisX7yOIA1RfQj4r+hEyas6e5vt86pGucEh6XP6QEuMAHHFriJWD3/NI9CZEvPNEPNtnmUSLXV2XV7V6NjhkBKnALZAwBUEyiooDil8FLeQzD8tpIuGUkIatk20f17VKGQ4JPPPNbQIAkUlQL2DVFfU3rqzcWJe1Y8b7Z9XNWpoOCR3nu+GjRordoah1U0xMcYOWRp0Iy+uqOt1hMeKpKY3HJBXNQoHDkn8HIEkCDiBQIf+fQjDaNwwnyANUX0IeIdXyD5RVbJnyXIH5FWNDhcOSdTqkBMhgAmSCKXiyhAnSLiDVARzEfOqvsX8ReikEU3CIRlBFTpBwLIEfNRbSJYdiYM71udywtvIvfvfY2GHwIBDcoghMQwQECNQPuYUMcGoVN30XQRpiOpDoOzqVpS8qp8c8MEh6UMeWhxFACt21jcnJkjWt9EZ1LyqjplYOGYg1j/J0EMQsACBtr0vJfQiuHsSQRqi+hDwVF0ovmKneNdMJ2S906eHhmmBQzIMrQsVDyeNuYYkDWF9CBAnSAhp0Ac7SUvbG1hQ+F0SMpvAShSSfgsLwyFZ2Dj269pcUpcrSNIQ1oUAMcYODyHpQp2mpPvVTPzC7DnukLyqUUbi46YhhTQIgIAFCXQe2oXQq/qlawjSENWHgP/y08JeUVWyNGeLM/KqRkcMhyRqeMjlJICQhpyIii6ACVLRTZCzA6fdxOScQjEBhb0hfr8pVsm6f+GQrGsb9AwE9CZQ1o2SV1U+jltIelsgtz7pouGUvKrVHzskr2qUDBxS7hMEEiDgFALlY4VvlvMh13103CkDt9E4Wl1LCmn4uN4vPp+yPAY4JMubyDYdxIqd9U1FjLFDSEMRTNr1emJe1SL00bAm4ZAMQwvFIGA1Au0v6UfoUuPGuQRpiOpDwDvsXEpe1c8/l0L6NGwJLXBIljCDEzqBCZL1rUicIOEOUhFMSs+r6piHkDhtOKQinHJoEgSKQsCLGLuicCc12vsKQtSc98AEx+RVjVKCQyKdLBAGARsTKL/yVELv62bsIEhDVB8CpVe1puRV/XS/Y/KqRvnBIelzGkELVuysfw4QV+wQ0lAEk9LyqrLxDlvkgkMqwjmHJkGgGATa9hpCaDa092OCNET1IeAZdLH4ip3iXfupc/KqRgHCIelzHrleCy2vqutxFQUAcYKEkIYiWImYV/U9B+VVjdKGQyrCSefIJudSRlVTQZGGrD4EaCENJ7Bipw92kpbzSHlVT7xFSDJE6kexhOGQikUe7YKAuQQ6X9aN0GD9slUEaYjqQ8A/upySV3XuJgflVY0ShEPS50RyuxaENFj/DOg8ltLHOkyQKLh0ku3k4ryqUYRwSDqdSVADAtYmUNqVlFe1DreQzLendCEpr2rNR07KqxrFDYdk/lmHFkGgCATKxwq/Y4f3ru6jo0Xoo9ubbHWth/Kq2IknnZRXNWp8OCS3fwd0GT9W7HTBaKgSYowdVuwMtYa68i6kvKrBN9S12LkUDsnO1kPfQUCUQPuLLxAV5XJNm2YTpCGqDwHv0O6UvKrLljhuxc5hj/nqc1pAC5UAcYJEVQ95HQhggqQDRINVnHoTITGdwt522kNIHC9mSAafY1CfSaAiswglBhMg5lU9gZAGgw2ipr7XleJZGpj34LsE96XWnBXL4JCsaBX0CQR0JlB+eQeCxrpZ1QRpiOpDoPSqNpS8qp/tc1Ze1ShEOCR9ziVXayGu2FW4GlaRBo+HkIoEntDs6TcShJnj8qpGBw+HRDoHIAwCtiTQpudQQr9DtYixI+DSSdQz8BLxFTvFu36a80IacA9Jp3PJ1WqQV9X65qelsav70EkvIbW+dZp72OYGRnkIiedVle0yNPF+YoYkzgqSGgTmapSrFtdUqBaj0FACiLEzFK8uys+7hhBj5qlzXF7VKEQ4JF3OJSgBASsTOO2yCkL3GpZ/QZCGqD4E/KNOp+RVnbfRE9KnYUtpgUOylDns2BmENFjfarQJEl48UQyLdqTmVfUVo5dGtwmHZDRh6AeBYhMo7UJJ9C0jr2oRDCZdMIIS0rDzIwc+hMSxwyEV4dxDkyBgKoHyMZRf03UTD5vaOzQWIdDqWm9Q+Goss0kn/GEnghNG4MTBY0w6EMCKnQ4QDVaBh5AMBqyD+rNJeVVD43Vo0ooq4JCsaBX0CQR0JHDqRRcStDVtmUmQhqg+BLxDKhXhaazsWb7IiQ8hcZRwSPqcT67VQpwguZZTMQdOC2nAq2KLYatTbiJ4GGfmVY1ih0Mqxtnn3jYr3Dv0oo3cQ30qtmg9dXHDtLyqX73LHPhQbMT8cEgu/hJg6K4gUD66E2GcJ2dvI0hDVB8CpWPaiedVldn0PT4nPoTEWcIh6XNCuVULccWuwq2cijlu2gQJDyEVw1blNxFaVZyZVzVKAA6JcCJAFATsR6BND0qywdAB5FU138aeAQMoDyFtdGRe1Sh2OCTzzz4HtUi51Dlo2LYaCm2CVPehIx9vsbjFiHlV35edmFc1aiM4JIufqhbv3lxK/2oqKNKQ1YdA5zEUPYixo9DSS7aClFf15JvMsdnY4ZD0OqegBwSsSKDTpecRutXwxXKCNET1IeAbdSYlr+r89Z6gPg1bTwsckvVsYp8eIaTB+rbCQ0jWtxExr+qbTPgRWuuPPa2HcEhpQLBLIICzhwCrOKIlpLyqCvKqFsFM0oUjKSENuz50Zl7VKHlcUopwAjqmSb9jRuLYgZx5VQlhbCcmfUWQhqgeBCTW9npfUPhCLLPJx5yZVzUKU5iDHuihw1kErp1OGU9NBUUasvoQ6IqQBn1AGqZFYeddxyRh9VLYqXlVowjgkITPBAimE6D89k6vi31TCJzWn5RXdVvAlF6hkQQBiZWN7EHJq7piASHrXaIdm2zBIdnEUBbs5rc+pHSqhiIMWZ0IVFxOUYSYbwotvWTPvo5wT8jBeVWjPOGQ9Dqt3KenlDbkCpo4pHUg4KkkPbqMkAYdmBNVKNLAoYQMbp7Djs2rGgUHh0Q8fyAeJ4CQhjgKq270GNqR0LWTc7cQpCGqBwEPK7+iTVj4MixLgV1OzasaxSlMQg/40OEkAg+8TBlNTQVFGrL6EOgzhKIHK3YUWvrIKuz8kQRNTs6rGsUAh0Q4GyCaTIC4YpdcFdvmEOh00SWEhsIHkVeVgEsXUUlpPaKn+Iqd4v1yipNDGvD6CV3OKlcqeRgrdpa3e78qShdPfOjYhDQUDKbKelivESwsHPQtsw/Cjs2rGgWPGZKp55+DGiv5I2UwNRUUacjqQ+DiARQ9WLGj0NJHNswuu4TyEFK9g/OqRonCIelzYrlPC1bsLG/zfoPOIPSxYdXnBGmI6kHAy84ZfaoifBGWPQvWOjevahSoc7P06XG+QIcmgTe/rXlI5UBNhUohigwmMKI/pQFMkCi09JGV2JWXMkV4xU5hPK9qkz5NW1SLsHO2aP/RrSIRKC9Su2hWmECH63oJyzKmwCERaOkj6gm1ueVs8RU7xbvnA8IztPr00WQtcEgmA0dzIGASgRv6eAkt1U3ZT5CGqB4EfOz6IZL4BInnVT3q4LyqUaJ2XrIjOFPhSbEep5kbdOzvTBllTQVFGrL6EBh3JkUPJkgUWvrIhtgDp4j7I+bwvKpRpoSLuj420FELIe4YaUB15B5R1YmkD78HSLj0ER46qhVBUbDmM4I0RPUgUCJfMko85JvJnlXznP0QEodqZ4dE8DIICdPjC5TQIR4YFKlzmGCpRBvYKohAh9tJ1JsmFtQaKtMJSE3sIYqDCbP3WYlCb8dWNey8ZEf4wsEh6XpWXkXURlo7IuqGuCqB0lF3qZZrFSofaB1BuTEEJMV7852MsMzj4zF2sjF9sY5WzJCsYwv79IQYYoefA+abts8NlAU7Ji/cYH4f3d2ih3W9sSQkegFWWFCaW+3ovKrR00GUhxXPHcJ1jhJuZMWhWqtPr71O608bmjikdSAwmpKykzHpHR3ahAoKAZldd6V4yLfEJ0cvMedfx+zskAizXcqJAlkQsD2B8286jzSGhjdJ4hAumIBf6X7X6QQPI5c2vc2cn2zQJfeQCj59oCBB4HjbxDa2LEnAfzvlzeV8COMbLDkOB3dKYd8bJB7yrUjB0reCpY0OBmL/of1EEf/Yf7SWGcEIcerNkpbpuWs6UnL5YZlmJdoCn2tAGjZQiXmuqFPCBCMFlUsoERCG9dxgxW5ZshtsMEcXqR/morHadKiXPtCe9ujXpvU2HanVui2GXWI+dvFPWwtHNPBRhn071zs8r2rUlnZ2SISwb0YIgLDaOW6x/kz7LbFDI/FjgEisYPG7RxFVzCCF5BGVu0aceyOFSQI+SeERCj+5gvQQqMymlzo+5pufKXZ2SBQnQ5F1zRcoMdA7Eps5th4YmkMg43DpkowiFNAJlA4RfZfE2ffdRkrsxPsy+yt6h1AjjYBX8fdtyxQlt0vysrZ33llCufgqfjbtRFp7jty1c1DDKQSLUGZTBLVOEX2dsX8LjWXWKCGxZCGgT6aR9/bdNy1cvW17Xe76bW67kzrfWVgtoDd3y66WkBR/+J4fv7l0Qy0PhZP4VCnLR2J3/4xnAsoikX4o7Fu1xg0TpPRx22r/TcItwdtsNTKzOxsBeccdAtOkMcR75VwvyOtjzSWKsum1740+J5e2jvcepdwrj36Hnq7IpRXHcxPwsvWKsvut7/fvwGUlj+bSHQ9ouPdklLv4PyHlL6eKP7SUu6+QMIBAQNyeyo8MaN85KltA5vJJP2cLCMhbREFel/OkKoozPO8P3xzQMYvCskG/rybb6Mj3nP/AZRZmOh3yswuVBv6DTV7x9E3dy7hST3QKlOGXStk5v69XQiQrycrJezMU6dRvqNGLwBqCTX+tV6NO1JPgeMcd39Me4A1NCUHxLZDXJko48tcY8T3v/ef156svg3pY6XeWHosJiv9deB2hIxDVIFDKnlUalVCQcz805T9Hd404eX+qp5eiIQ+3rZdJAd9cYVhZM5Jyy0mjiyg2lMB+8a+c8qyhPbG58hSOP378CbXhDB7MKLzjKgFejSa97Ks4UUVZ/dqjX++ZqaJj3+89d4y+pqoo73TPVIYSIgE+HToWnffIwciS6dZ3Hr3qLK6ixMO8fubxRv6LTJtO//bLihJxWsTPx2e4wyHZOaiB8k6e04inl3vF/8JYu663pI3//k1vExOqxhQAfIxEQX/HJa/TXXDByXU1+1d8trNbbcuj+6WN7doP7P+tDu3zSaf1Vc3WgvqGyvyWkeJvvLldyBcJ+/YxWfadd97Xtm3ZseST/e1OhsM8ytsbZqyh04ARd3SLPFNERta4cZ/kiqAGOy9MZg1kSTP57NFpBdiNE1DhuLTrGTcPHHjVbV+/9ZE/Pv6ThezrxyghjXHNPJ4Y3JNo5L859Zr0ukfrWy3dUn9gWZs2ayo6+Pu1Ht7mTH9+3+Zt/+/tdOXYJxPwBxdderwdr8Z9Ev83HElTF/KEl2w5uH/Bqa2WV5zuH9z2+rJ2Sh7eiOs8ftdHzs/0TWZurQpXUSa926zVd0v1RpPjIeWd48ouzcMiB8BdF1N34PFbap/6A/W1W+t3HlFOkiPrEup2n65LH92upN1ejrQhep81um4qc5NEQhf4/8ePK4ebeednJlk50MEdK3Z2PonuSHylcm85P01uIabMzS9fCXAvxC5Jda94Ja+QEgG7ye8nNYPNfAnwadFlb/CbQ+GGiBeSW+7lRW4oBUNKKKw0EQPrki3XpExh6nEs+fbWsvUoD2dZbBBnU/rju5Qi7TZZKffD5XkiGZ5nPVRLIzDjno4PzEsr02dXWnaqPorcrUUplRaNa3ffMk+pt6kpkq0huhIu+TzM51W8Hp4YNTXijkLLwxa2rARSatlS1sYOqTcJeAVJ2n3CBrkkYNftVDrxjxGXPLVXN3VxRUe2HI9vYyN/Ao1KSWnDy4N6P3OopERqDCY/xprfvb14VxTvyQ1SMHvyh7iwzTds7JD6kdD3Ikm7UdiQaRKw63kqrXzkrG9+pKfCiK7NJ10RvqU3tgx9Emtq9Jb6vvxZpxs/YaX+UKOOWHd+Jf7qpIyOocAcAseTV1lzbn9oTqds30pOkCQBUNf/hOjyGOWJ8NzmWthX/z66U2N0IuSP5HHu/PMtHHxDY4R+Pk+GpVttzTmIabD6OTUi3WjZ97dbfTyW6V92jrSjoG6IWUe/VE+zQxbp4HRDuuhSpRGfJJVGAhAu/RePQmmOcMhCX+hQkzI3eQHQ0Wjtu2RHfE9chaPNqOfg9Fy6O1fPjkFXjMCs+zp+f05sp8C/vtkFKkD1JAKRSAalsclX6ll8V9vvLm2OcIiUJcnksTnNNS90s69DosZv3Z3HeeDWKrpFOAC6QadQ/T9HXfjkbl2U17fRRQ2UxAlIjN9AKiltem1wzz8ejEc45O+T/CwoNcW1O3vDvg5pKNEwY4ny7hbXaZoE6MadRmse7fKNDwpXv78M70IqnGKKhqjraWr0lPo2/7zzdVNaIhyid5hS5ER35CaPkr87E20FcgUReEBo9TVJ6EBBzbmzchK+vDbB3Ojz5qyfr8rLMolKdXhhlSFGivqfaIRDp4c3cdwFRDg0KV/jjzHhY2kCsxJfKcGtr1l6PBbtnCBbLTEwN96uI16s08IvUt54FT3Vp/GDckQLEZ8klUQiHAa90sDD7RryyPIdNWHoCgTZWfyMyOPVpRMtPiSrdk/kqqYlA+ZmWLX0nplaBshdvut+M7ro5ja8pfzGiP+OhdwWjZE3+JEDwcMn73ZNlJ1dT5Q8Xl0aqrLrYIvd79xXNQ0JIDfLdP1+t0PDBrmKw9+NPDiDj1EEokt3JRHG5/2+lhsjKf1qLtPEjoeU7zBMY40ykC56fx6zFeUvkuznz57COUkWyPNHTq1504Qk8OKbdY/aN7CJiqiI8jzCgbd+9cfcMMFo+lVxC/EaPytiz9F0bgL5vUxbuSO3ZkhoEqB8g+KymtpwQH8CZ/zsizh44Y3gc2317wk0qhDwRaZJHX66kZuGFuEQUl7EDEkFqHWK8nqZtqIcID5Ma50BW6Mnwhe5uCB+AphsuWHP0zJqcUt90svkPrqzuUSEw4BIng1ahMPneGWVhc+awTXxCx5x48AoCw/LFl2jAsdPALPN6r97OslI8p4ro7c5zO6nS9uLRjh4x83nNmpqiLyuTyjVXcMIRDVY9oQZHbk1mOfnqxstOyy7dIxGHj8BimDXPv+7nWClxvGkN4sVYTzOaTLq+qMPJ1X8Nu0Fs9ksFlbexY8Gq54F9x/NZrpcx0L/Z9Vx2ahfuSAnHccvgOLY9Ya3k4yQY3Pf1yKPyuBjHoHmCIcxH3LDhIQiHIL1IzFFMs8+lJY+yPHtynl4HjUJHqV3rpHNiTkmEHINEosNtPyny2I2yPG38bXTLNZ3F3QnGuHQ/sfruG0aG3M+nCQrb7b1YpJkvfPi8X05vlwCh4OvWG9cNuyRAOmICKakxbPtkGePCFlpx73F66M7W474luYcDpf8g+fZEIhwCI/jyRrgkqx1ujyyS+j7lVPoxCuYJelh2ZygIwKYkeqBOk8dnjs/FTHSuqvK8mwA1Qoh4C31csd02xxuoxwRDmGlGs/1F4Ja/7q3vUMOaM3yXZz3qP49dKHGLITjh4Iu5GKhIfd8YmvcFFobwff7WKjHbulKdL4TjXDo9sRubpqsORxCypRuHmRYtci58fXffnpI68uUd/nq5x+ivsLCIjgs1Y3c/LFEWmSDXftmLiN99bsid9GlzUd8kqc04mcuf4/bKHuEgyvisay3Kpn0LGVZqzat2nXt2vUMw3p5Yuee3XuPNdbXJ+6975zt0i9H/sPO8a6WunfvyV83aupBoNPt4wZl1dP03Isbc5gxa30cLISAz9vI2Cl33n8+Y03Mz692SuYVjxf97cldfqw3FAI6n7q5fswZffzlfDrt9jo5jIJbdsU/QQb/LesiQ80TeHFskYwUcT7NEQ4XPhe5LaHxloqwfPi3El5DYbqRclzbDD8Mh5SfybMaBrfs8oOqb61x07IY6cTrl+nbGrTRCEQjHNg3Z3EbaUY4vNGX+XgcBD4mEsjynTHlEBxS3sbOYh/EkORNVc+KPX65WdNIX/3jTD2bgi4SgegaXTTCocsvd3IbqUU4BMP1LyEckoRVB2HNL4xJB+CQCjCito1WP1+AWlTVj8DV4zWNtO3h3vq1A01UAhGf1BzhMOpdbiP1CIe9PzmL+fByJCrbAuQ1vy4mHYBDKsB4vKqmmRDTWBhY3Wp3+OFidSPJ6/9yGSKLdeOcp6JoDoe2D67iNsrI4RBqUHY/dwnjLikz6iHP5lAtBwH174p5pXBIOQyU87CmrXLWhIBJBAb9+aC6lb786RkmdQHNqBJIRDic/7dI1k6VCIedP+jIq3rgklQB6l6o/kUxrxQOSQeTqptr/fqADrqhQhcC356sZqTwoWW/GKCLfigphEBzhMPNAW6jtAiHUEhRVj4aeYeV5ESfZD03W+ynIV5BYq9Cvknxuup2/MOxxqfjItgoKoHzxt3eM7MDSvUXC1esPZB5ACWmEZAiXx6/hz+cdNa993VjrDGaoyH2cFJY8hxa+sn8L09wn8TUv2am9VT3hqznkHQfIhQWiYD6d+Xh+vpXi9QhNJtOYOy42z3pZYwdWL5oxabteAQzk4x5JRGf5PHL3AjDH/qWh4VDaeHex1fOnL3hgOw4nwSHZN455sKW1H3SnYz924UwLDnkU8eNG6LSsZULFm3fvlflAIpMJeDzNims9e0P8ECG5hwOza3LkQdkN8+evarGadMkOCRTzy/3NabuktidcEmWORcGjBtXntmZ4wsXrty+nV/v8Ckagcg0SfJzV8T63n9ne750540HfMsKf0C24fOZCzbu47Oo6Bpf0bqpZ8NwSHrShC41Auo+CdMkNVZFKrt13A0qLW9ZuHDT9mqVAygylYDXFwoz9rWHxjAWCvv53EiJvBlJkRn3SXvmzVq27bCp3UFjIGB3AmoBXYpyxyi7j8s5/T/n/61XMZI8/8mxHZwzSFuOJDpniOZwOOMX27mNknI4hIORd82u+PPVbW05MnQaBIpGQOVqpygIsS+aPVQavvLVpkwryX9vpyKKIlMJRHxScw6HoeN51He4gf+jyBFnpISC/J+XWuFlsqYaBI05gUDk+5P6gUOyll3bPjAv1UCKsvlH1uqim3vjK+WeqezeZdxGLTkcIj4ppOx9KLJ4hw8IgACNQNrVDv6Ihs8M6Yuf2ptipU+yv0fJjC6hjSiB6NJdSSnf7vVM5E0izTkcIi5pQR84JJwkIJAXgeSrHRxSXgiNrnTLRwkjHfmT0a1BP42AtzQSaXdD5E0iwYYwX7lT6rmNot6KpgjSIAACEQKxy93LcEgWPSG6Pra2xUjLb7VoF13arajjiUY4lD+6lduooSmsbLuRxaPBXYoFwwaBQgg0X+3gjwphaHDd0S83RKz07jkGtwP1VAIRnySVlvB/L3udR6GEmz7sjBU7KkTIg0AqAX6xg0NKRWKxvdbfm6PseNxinUJ3YgSiEQ6l3+VvEvkF3mseg4K/IJA3AfijvNGZVfHC+9XSCpnVOtrRJpCIcOj5H/2xYqcNCkdAAARAAARMIeCJRjggpMEU2GgEBEAABEBAi0B0mpSWBVxLFuUgAAIgAAIgYCSBqE8ysgHoBgEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQsBYBqZT3JxS2VqfQGxAAARAAAfcR8HXkYz5W576BY8QgAAIgAALWIuCxVnfQGxAAARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcSgENyq+UxbhAAARCwGAE4JIsZBN0BARAAAbcS8Ll14JYet5TaOyV1F3sgAAIg4EgCcEgWNGvnNKvstWAf0SUQAAEQ0JsAluz0Jgp9IAACIAACeRH4/+Tz+cof5vLgAAAAAElFTkSuQmCC",
      "text/plain": [
       "540×1680 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)        …  Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)        …  Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)        …  Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0)        Gray{Float64}(0.0)           Gray{Float64}(NaN)\n",
       " ⋮                                                   ⋱                    \n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)  …  Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)  …  Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)\n",
       " Gray{Float64}(0.0980392)  Gray{Float64}(0.0980392)     Gray{Float64}(NaN)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rot_deg = 21\n",
    "tfm = recenter(RotMatrix((2pi)/(360/rot_deg)), center(img_ori))\n",
    "imgs_rotate = [warp(img_ori, tfm, axes(img_ori), interp) \n",
    "    for interp in [Constant(), Linear(), Cubic(Line(OnGrid()))]]\n",
    "\n",
    "[img_ori hcat(imgs_rotate...)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "事实上，我写了一个`imrotate` wrapper来完成这一工作，见[JuliaImages/ImageTransformations.jl#58 (comment)](https://github.com/JuliaImages/ImageTransformations.jl/pull/58)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "imrotate"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "    imrotate(img, angle; fill = NaN, method = \"nearest\", bbox = \"loose\") -> imgout\n",
    "\n",
    "Rotate image `img` by `angle` degrees in a counterclockwise direction around its center point. To rotate the image clockwise, specify a negative value for angle.\n",
    "\n",
    "# Arguments\n",
    "- `img::AbstractArray`: image to be rotated\n",
    "- `angle::Real`: amount of rotation in degrees. The rotation is in counterclockwise direction.\n",
    "- `fill::Real`: filling value for pixel outside of original image. Defaults: `NaN` if the element type supports it, and `0` otherwise\n",
    "- `method::String = \"nearest\"`: the interpolation method used in rotation. Options are \"nearest\" or \"bilinear\"\n",
    "- `bbox::String = \"loose\"`: the bounding box defines the size of output image. If `bbox = \"crop\"`, then output image `imgout` are cropped to has the same size of input image `img`. If `bbox = \"loose\"`, then `imgout` is large enough to contain the entire rotated image; `imgout` is larger than `img`.\n",
    "\n",
    "See also [`warp`](@ref).\n",
    "\"\"\"\n",
    "function imrotate(img::AbstractArray{T}, angle::Real; fill = NaN, method::String = \"nearest\", bbox::String = \"loose\")::AbstractArray{T} where T\n",
    "\n",
    "    # FIXME: Bicubic method does not support N0f8 type.\n",
    "    args = []\n",
    "    push!(args,\n",
    "        if method == \"nearest\"\n",
    "            Constant()\n",
    "        elseif method == \"bilinear\"\n",
    "            Linear()\n",
    "        else\n",
    "            ArgumentError(\"method should be: nearest, bilinear\")\n",
    "        end)\n",
    "    if !isnan(fill)\n",
    "        push!(args, fill)\n",
    "    end\n",
    "\n",
    "    rotate_fun(img, tform, args...) =\n",
    "    if bbox == \"loose\"\n",
    "        warp(img, tform, args...)\n",
    "    elseif bbox == \"crop\"\n",
    "        warp(img, tform, axes(img), args...)\n",
    "    else\n",
    "        ArgumentError(\"bbox should be: loose, crop\")\n",
    "    end\n",
    "    \n",
    "    tfm = recenter(RotMatrix{2}(mod2pi(1*angle)), center(img))\n",
    "    rotate_fun(img, tfm, args...)\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "540×1260 Array{Gray{Float32},2} with eltype Gray{Float32}:\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)        …  Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)        …  Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)        …  Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0)        Gray{Float32}(0.0)           Gray{Float32}(NaN)\n",
       " ⋮                                                   ⋱                    \n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)  …  Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)  …  Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)\n",
       " Gray{Float32}(0.0980392)  Gray{Float32}(0.0980392)     Gray{Float32}(NaN)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rot_deg = 21\n",
    "imgs_rotate = [imrotate(img_ori,rot_deg*pi/180,method=method,bbox=\"crop\")\n",
    "    for method in [\"nearest\",\"bilinear\"]]\n",
    "\n",
    "[img_ori hcat(imgs_rotate...)]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.0.0",
   "language": "julia",
   "name": "julia-1.0"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.0.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
